Title :
Neural network routing for multiple stage interconnection networks
Abstract :
Summary form only given, as follows. A Hopfield model neural network can be useful as a form of parallel computer. Such a neural network may be capable of arriving at a problem solution which much more speed than conventional, sequential approaches. This concept has been applied to the problem of generating control bits for a multistage interconnection network. A Hopfield model neural network has been designed that is capable of routing a set of messages. This neural network solution is especially useful for interconnection networks that are not self-routing and interconnection networks that have an irregular structure. Furthermore, the neural network routing scheme is fault-tolerant. Results were obtained on generating routes in a 4×4 Benes interconnection network
Keywords :
fault tolerant computing; multiprocessor interconnection networks; neural nets; optical information processing; parallel processing; Benes interconnection network; Hopfield model neural network; fault-tolerant; generating control bits; multiple stage interconnection networks; parallel computer; self-routing; Computer networks; Concurrent computing; Electronic mail; Fault tolerance; Hopfield neural networks; Multiprocessor interconnection networks; National electric code; Neural networks; Routing;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155452